CN114786240B - 5G downlink signal intermittent tracking method - Google Patents
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Abstract
The invention relates to a 5G downlink signal intermittent tracking method, which provides an intermittent signal tracking method combining DLL and Kalman filtering, deduces a signal model based on a 5G intermittent signal tracking loop, corrects a traditional DLL code phase discrimination function, and takes the output result of the discriminator as the observed quantity of KF filtering. Meanwhile, the method is provided for the first time for compensating residual frequency offset on different subcarriers of an OFDM signal, and reducing the influence of the frequency offset on code phase estimation. Furthermore, from the aspect of the multi-dimensional resource joint optimization of the time domain, the frequency domain and the space domain, a signal tracking scheme for joint positioning reference signals and channel state information reference signals is provided, and observation noise in the tracking process is estimated and corrected in real time. Compared with the traditional DLL tracking result, the tracking loop processing method provided by the invention effectively improves the code phase tracking precision.
Description
Technical Field
The invention relates to the technical field of 5G positioning, in particular to a 5G downlink signal intermittent tracking method.
Background
With the advent of the 5G age, the internet of things and intellectualization have placed higher demands on location-based services. Support of location services is generally required in the 5G three-major application scenario defined by the international telecommunications union Radio communication office (International Telecommunication Union-Radio, ITU-R). Among other things, enhanced mobility broadband (enhanced Mobile Broadband, eMBB) features high-rate, high-capacity communications that require accurate positioning of devices to enable location-based media services. Ultra-reliable low-delay communication (ultra Reliable and Low Communication, uRLLC) is applied to the industrial field and accurate positioning of unmanned vehicles and unmanned planes is required. Large-scale machine-type Communication (MASSIVE MACHINE TYPE Communication, mMTC) is oriented to the internet of things and sensors, and related positioning requirements include positioning and tracking of materials and personnel. For a few main positioning systems currently in mainstream, the global satellite navigation positioning system cannot complete positioning under shielding and indoor environments due to limited number of visible satellites; the wifi fingerprint positioning has reliability and accuracy problems in the construction and updating of the database; UWB (Ultra Wide Band) and bluetooth AOA (Angle of Arrival) positioning systems can realize high-precision positioning, but have the problems of complex construction and high cost of the system and limited signal transmission distance. The design of the 5G communication system makes the "5G positioning" a new direction for solving the ubiquitous high-precision positioning problem. The transmission characteristic of the 5G high-frequency band and the large bandwidth provides high time resolution and multipath robustness, provides a basis for a time positioning scheme using a first path measurement value, and improves positioning performance indexes such as position accuracy, speed accuracy, time stamp accuracy and the like.
However, due to the characteristic of intermittent broadcasting of the 5G reference signal, a traditional delay locked loop (Delay Locked Loop, DLL) tracking loop cannot perform long-time coherent integration on the signal, tracking accuracy is limited, and loop robustness is poor.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention aims to provide a 5G downlink signal intermittent tracking method with high tracking precision.
In order to achieve the above purpose, the invention adopts the following technical scheme:
A5G downlink signal intermittent tracking method comprises the following steps:
Step 1, receiving a 5G signal, wherein the 5G signal comprises an on phase and an off phase;
step 2, searching the cells;
step 3, performing coherent integration on the processed 5G signal and the local signal to obtain coherent integration results of the instant branch, the advanced branch and the lagging branch;
Step 4, sending the coherent integration result to a discriminator for processing: for the 5G signal in the on phase, the discriminator outputs a code phase error discrimination function δτ, a carrier phase error discrimination function δφ, and a carrier frequency error discrimination function δf d; then, the signal-to-noise ratio of the 5G signal is estimated according to the coherent integration result in the on-phase and the coherent integration result in the off-phase, and the code phase covariance is calculated according to the signal-to-noise ratio Carrier phase covariance/>And carrier frequency covariance/>
Step 5, the output of the discriminator is sent into a Kalman filter, and the Kalman filter predicts and corrects the state;
And (3) predicting the state to obtain:
Wherein, A priori estimating vector for the system state at the current moment;
estimating a vector for a posterior of the system state at a previous time;
F is the state transition matrix of the system state vector at two adjacent moments,
Estimating an error covariance matrix for the prior of the current moment;
Estimating an error covariance matrix for the posterior at the previous moment;
Q k-1 is the process noise covariance matrix of the last moment;
The state prediction and correction are carried out to obtain:
Wherein K k is the Kalman filtering gain at the current moment;
h is the observation matrix of the sample,
R k is the measurement noise covariance matrix,
Estimating a vector for a posterior of the current system state;
z k is an observation vector, and consists of the output result of the discriminator, namely Z k＝[δτ,δφ,δfd]T;
P k is a posterior estimation error covariance matrix at the current moment;
Step 6, the kalman filter outputs the code phase error delta tau k+1, the carrier phase error delta phi k+1 and the carrier frequency error delta f d(k+1) at the next moment and sends the code phase error delta tau k+1, the carrier phase error delta phi k+1 and the carrier frequency error delta f d(k+1) to the reference signal generator.
The step 2 specifically comprises the following steps:
Firstly, the received signal and 3 groups of local PSS signals are subjected to related estimation to determine
The position of the correlation peak represents the SSB symbol start time for controlling the FFT window;
frequency offset estimation based on CP
After obtaining the initial frequency offset, carrying out frequency offset compensation on the received signal to obtain
T s denotes the sampling interval, satisfying T s =t/n=1/(nΔf), T being one OFDM symbol effective duration;
Then receives the signal Performing FFT operation, extracting SSB resource grid signal, and performing correlation estimation with local 336 SSS groups to obtain SSS sequence ID with maximum correlation peak value as cell group/>
Obtaining the cell ID number of the base stationThereafter, local PRS and CSIRS signals are generated, and the received signalsAnd performing correlation estimation to obtain a signal r cc (n).
And step 2, adopting a channel and time delay joint estimation algorithm, wherein a processed signal model is as follows:
Frac{τ}∈(-Ts,Ts)。
In the step (3) of the above-mentioned process,
The instantaneous branch coherent integration results are:
IP＝real(P),QP＝imag(P)；
the result of the advanced branch coherent integration is:
IE＝real(E),QE＝imag(E)；
the lag branch coherent integration results are:
IL＝real(L),QL＝imag(L)。
In the step 4 of the above-mentioned process,
The code phase error discrimination function is
The carrier phase error discrimination function is
The carrier frequency error discrimination function is
The carrier-to-noise ratio of the 5G signal is
Wherein,Representing the result of coherent integration in the on phase,/>A coherent integration result representing an off phase;
code phase covariance is
Carrier phase covariance is
And carrier frequency covariance
After the scheme is adopted, a discontinuous signal tracking method combining DLL and Kalman filtering is provided, a signal model based on a 5G discontinuous signal tracking loop is deduced, a traditional DLL code phase discrimination function is modified, and an output result of the discriminator is used as an observed quantity of KF filtering. Meanwhile, the method is provided for the first time for compensating residual frequency offset on different subcarriers of an OFDM signal, and reducing the influence of the frequency offset on code phase estimation. Furthermore, from the aspect of the multi-dimensional resource joint optimization of the time domain, the frequency domain and the space domain, a signal tracking scheme for joint positioning reference signals and channel state information reference signals is provided, and observation noise in the tracking process is estimated and corrected in real time. Compared with the traditional DLL tracking result, the tracking loop processing method provided by the invention effectively improves the code phase tracking precision.
Drawings
FIG. 1 is a schematic diagram of an SSB structure;
FIG. 2 is a diagram showing PRS resource distribution diagrams under different frequency domain densities, wherein (a) (b) (c) (d) respectively correspond to the frequency domain densities 2,4,6,12;
FIG. 3 is a schematic diagram of a discontinuous PRS;
FIG. 4 is a schematic flow diagram of the acquisition phase;
FIG. 5 is a schematic flow diagram of the trace phase;
Fig. 6 is a schematic diagram of discontinuity tracking based on state prediction.
Detailed Description
The 5G physical layer supports a flexible and variable parameter set with a subcarrier spacing selected in the range of 15KHz-240KHz, the larger the subcarrier spacing, the shorter the OFDM symbol time. One radio frame in the time domain is composed of 10 subframes of data, each subframe is fixed to 1ms, and the number of slots in one subframe and the duration of each slot depend on the subcarrier spacing. The bandwidth in the frequency domain consists of a number of physical resource blocks (Physical Resource Block, PRBs), one PRB comprising 12 consecutive subcarriers. The time-frequency resources occupied by the signaling are finally mapped to individual grid cells, which are called Resource Elements (REs), and are also the minimum units for Resource scheduling.
The first step of the receiver for the signal processing of the base station is that the signal must be converted into a frame structure in order to be able to extract the transmitted information, which is achieved by identifying the frame start time. The Synchronization Signal (SS) and the Physical Broadcast Channel (PBCH) and its associated demodulation reference signal (DM-RS) in the 5G standard are combined into a Synchronization Signal Block (SSB), where the SSB occupies 240 consecutive subcarriers in the frequency domain and 4 consecutive OFDM symbols in the time domain, and the structure is shown in fig. 1. The SSBs form a synchronization Block burst set (SSB Block), the SSB Block is periodically transmitted for 20ms, the initial OFDM symbol positions of the carrier signal are different according to the subcarrier spacing and the carrier frequency, and the specific configuration information is in [13 ]. Meanwhile, the 5G designs flexible PRS and CSIRS resource transmission configuration, and resource overhead is saved to the greatest extent by adopting a mode that the number of resources can be dynamically configured according to specific scenes under a resource set. One PRS resource can continuously occupy 2/4/6/12 OFDM symbols on a time slot, and 24-272 PRBs with the step length of 4 are occupied on a frequency domain. The resource density Deltak in one PRB is 2/4/6/12, i.e. one PRS symbol is modulated every Deltak sub-carriers. Fig. 2 shows PRS resource profiles for different frequency domain densities within one PRB. FIG. 3 shows a PRS signal transmission configuration within 20ms, with a subcarrier spacing of 30KHz having 2 slots within a subframe, PRS occupying 6 OFDM symbols within a slot, defining a duty cycle asL on is the number of symbols occupied by PRS, L All is the number of symbols in one subframe, and the duty cycle in the figure is/>
The 5G downlink transmission scheme adopts the traditional CP-OFDM transmission technology, and the base station side generates a pseudo-random sequence of a reference signal according to high-layer parameter configuration. The PSS and SSS are formed of m-sequences of length 127, transmitted on consecutive subcarriers. Wherein the sequence of PSS is defined by ID number in base station cell groupInitializing SSS sequence by base station cell group/>And/>Co-initialization sequence,/>And/>Together forming a base station cell ID number.
The golden sequence for initializing PRS and CSIRS is modulated by a symbol and prefixed by a CP, and the data of the nth sampling point on the first OFDM symbol of the transmitting end is expressed as:
Where N represents the number of IFFT (INVERSE FAST Fourier Transform) points, S l (k) represents the complex signal on k subcarriers, and N CP represents the number of samples within the CP length. J l denotes the subcarrier position index where the reference signal is located on the first OFDM symbol. The baseband discrete signal obtains a radio frequency transmission signal through digital-to-analog conversion and carrier modulation:
Consider herein a receiver signal model under a single path channel whose channel response function is expressed as
The time domain signal received by the receiving end is
Because the simulation experiment is to process on the baseband, the signal model of the signal at the receiving end after the radio frequency carrier wave is stripped is as follows:
Wherein f d,k is Doppler frequency offset on different subcarriers, Δf represents subcarrier spacing, and since Δf in the 5G standard can reach 240KHz at maximum, when the motion speed of the receiver is larger, the frequency offset on different subcarriers has larger difference. In the existing structural design of the navigation positioning receiver, the influence of the error on the final positioning result is not considered. Therefore, the invention carries out residual frequency offset compensation on carrier frequency offset on different subcarriers, thereby achieving tracking results with higher precision.
The invention relates to a 5G downlink signal intermittent tracking method, which is realized based on a 5G cellular signal positioning receiver, and the receiver can extract, capture and track carrier frequency after receiving the 5G downlink signal.
1. Carrier frequency extraction
The first step of the receiver for the signal processing of the base station is that the signal must be converted into a frame structure, and this is performed on the premise that the frequency location of the SSB in the received signal is found first. Due to the design of 5G large bandwidth transmission, a newly added synchronization grid (Synchronization Raster, SR) in the standard is adopted, a receiver firstly needs to perform blind search on the whole bandwidth of signal transmission to find the frequency position of SSB, and then timing synchronization and frequency offset estimation are performed to calculate the ID number of a cell base station. The global synchronization grid is defined over all frequencies, SSB frequency locations SS ref, whose corresponding number is the global synchronization channel number (Global Synchronization Channel Number, GSCN), and GSCN parameters are defined as shown in table 1. The receiver side knows the signal transmission center frequency and GSCN of the SSB, performs frequency point conversion according to table 1 to obtain the frequency position SS ref where the SSB is located, and performs frequency offset correction on the received signal. If the SS ref is known at the receiver side, this step may be skipped to perform subsequent steps.
TABLE 1 GSCN parameter definition
2. Capturing
As shown in fig. 4, the acquisition process of the 5G downlink signal, that is, the cell search process, includes symbol timing synchronization and initial frequency offset estimation. Firstly, the received signal and 3 groups of local PSS signals are subjected to related estimation to determine
The position of the correlation peak represents the SSB symbol start time and is used to control the FFT window.
Because the CP part of the received signal in one OFDM symbol has a fixed phase rotation relation with the last CP length part of the effective symbol, the frequency offset estimation method based on the CP is adopted, and the frequency offset estimation can be realized without additional auxiliary information:
Because the noise immunity of the traditional algorithm is poor, the method combines the characteristic that SSB transmits on 4 symbols, and combines the CPs of 4 OFDM symbols to improve the precision at the expense of time complexity. Meanwhile, considering the influence of multipath effect, the former part of data of the CP may be interfered by the symbol of the last OFDM symbol, and the invention carries out correlation calculation after the data delay N 'CP sampling points in the CP during data processing, N' CP＜NCP. The improved treatment process is as follows:
after obtaining the initial frequency offset, carrying out frequency offset compensation on the received signal to obtain
T s denotes the sampling interval, satisfying T s =t/n=1/(nΔf), T being one OFDM symbol effective duration.
Then FFT operation is carried out on the received signal, and the resource grid signal of SSB is extracted, and correlation estimation is carried out with local 336 groups of SSS, so that the SSS sequence ID with the maximum correlation peak value is obtained and is the cell group
Obtaining the cell ID number of the base stationAnd then, generating local PRS and CSIRS signals, and performing correlation estimation on the PRS and CSIRS signals and a received signal r cc (n) to obtain an initial TOA estimation result. The channel and time delay joint estimation algorithm is adopted, the obtained integer time delay estimation result is used for controlling an FFT window after compensating the received signal, the decimal time delay estimation result is used for tracking the initial time delay of a loop, and a signal model of the received signal at the moment is as follows:
Frac{τ}∈(-Ts,Ts)
3. Tracking
As shown in fig. 5, due to the intermittent broadcasting characteristic of the 5G reference signal, the conventional DLL tracking loop cannot realize long-time coherent integration of the received signal.
(1) Tracking signal model
According to the shift in the time domain corresponding to the phase rotation in the frequency domain, the signal model of the local early code and the local late code can be obtained as follows:
Where ζ=0.5.
The acquisition phase is completed, and a fractional time delay Frac { tau } and carrier frequency error and carrier phase error remain in the received signal. The Doppler frequency offset between different subcarriers is biased, and the initial frequency offset obtained in the acquisition stage is relative to the center subcarrier. In order to reduce the influence of carrier frequency offset on code phase estimation, the invention provides compensation for residual frequency offset on different subcarriers. Based on the OFDM signal model, residual frequency offset compensation on different subcarriers is needed to be performed on a frequency domain, and FFT conversion is needed because the received signal is a time domain waveform, and sampling frequency deviation and symbol timing deviation can influence FFT conversion results.
Therefore, the compensation amounts for the different subcarrier frequency offsets are compensated in the generation of the local signal. Namely, the signal model of the local real-time code is as follows:
Wherein, Representing the remaining frequency offset on the kth subcarrier.
Then, the received signal and the local signal are coherently integrated to obtain
Wherein L represents the number of OFDM symbols involved in coherent integration, and the duration T coh.χ(fd,k of the coherent integration time is L symbols) represents the residual frequency offset error phase difference between different subcarriers at this time, and after compensation, the value can be considered to be almost independent of the subcarrier index, and χ (f d,k)＝Δfd, which is the frequency offset error to be tracked later) is recorded under the condition of no confusion. Further simplifying the formula, the instant branch coherent integration result in the formula (12) is calculated as follows:
IP＝real(P),QP＝imag(P)；
The integration result is also processed by the I/Q branch. The signal model of the leading and lagging leg is similarly derived by substituting the signal in equation (10). The result of the advanced branch coherent integration is:
IE＝real(E),QE＝imag(E)；
the lag branch coherent integration results are:
IL＝real(L),QL＝imag(L)；
real represents the real part of the signal and imag represents the imaginary part of the signal.
The coherent integration results of the instant branch, the advanced branch and the lagging branch are input into a discriminator as input, and a code phase error discrimination function is obtained as follows:
The code phase discrimination error obtained according to the above is:
Wherein Deltaτ 0 is the fractional time delay from the acquisition phase in equation (11) The frequency discriminator uses the dot product and cross product frequency discrimination algorithm proposed in document [17], and the carrier phase error discriminator uses a two-quadrant arctangent function.
dot(k)＝IP(k-1)IP(k)+QP(k-1)QP(k)
corss(k)＝IP(k-1)QP(k)-IP(k)QP(k-1) (17)
The frequency discrimination error of the frequency discriminator is the phase error of the adjacent integration time interval, and the discrimination error variance of the phase discriminator is shown in formula (20).
In order to improve the tracking precision of the receiver to the 5G discontinuous signal under the low carrier-to-noise ratio and dynamic scene, the primary estimation of the relevant parameters of the received signal is obtained through the discriminator, and then the filter processing is carried out on the received signal through a Kalman filter.
(2) Kalman filtering
The system state vector X k of the Kalman filter is the code phase error Deltaτ, carrier phase error Deltaφ, carrier frequency error Deltaf d and carrier frequency change rate error Deltaf α between the input signal and the local signal, i.e
Xk＝[Δτ,Δφ,Δfd,Δfα]T (21)
In the loop updating time, the state transition matrix of the system state vector at two adjacent moments is as follows:
the state transition equation is expressed as:
Xk＝FXk-1+Wk-1 (23)
F is a state transition matrix, and W k-1 is a process noise vector.
The observation vector is composed of the discriminator output result:
Zk＝[δτ,δφ,δfd]T (24)
The observation between the observation vector and the system state vector, the observation matrix is expressed as:
The observation equation is:
Zk＝HXk+Vk (26)
v k is the observation noise vector.
The specific process of Kalman filtering is as follows:
State prediction:
in the prediction stage, kalman filtering is estimated according to the last system state posterior And a state transition matrix F to obtain a priori estimate/>, of the system state at the current timeCalculating a priori estimated error covariance matrix/>, at the current moment, according to the posterior estimated state covariance matrix P k-1 and the process noise covariance matrix Q k-1 at the previous moment The size of (3) represents/>Reliability of,/>Smaller represents/>The higher the reliability of (c).
Measurement update:
After obtaining the Kalman filtering gain K k at the current moment, estimating a vector prior to the system state according to the observation vector Z k at the current moment Correcting to obtain posterior estimation vector/>, of system state at current momentR k is the measurement noise covariance matrix.
(2) Real-time estimation of intermittent tracking and observation noise
Based on the characteristic of intermittent broadcasting of the 5G signals, coherent integration calculation is carried out in the time of the signals, and the discriminator is utilized to obtain observables. And in the time of the next signal transmission, adopting state prediction, and initializing the generation of the local signal by using the last observation result. Fig. 6 shows state prediction based discontinuity tracking, where "on" indicates the duration of the signal and "off" indicates no signal is transmitted. Further, to improve the reference signal resource utilization, methods for combining PRS and CSIRS for tracking are presented herein. That is, unlike the manner of using a single port to transmit PRS to realize ranging specified in the protocol, the reference signal association is that the CSIRS and PRS are used to generate the same sequence, that is, the time domain and frequency domain characteristics are the same, and the sequence itself has good correlation characteristics only when the reference signal association is transmitted at different antenna ports. The joint mode is divided into 2 types, one is that the frequency domains are independent, namely, PRS and CSIRS occupy different subcarriers respectively on the same OFDM symbol, and the number of available subcarriers is increased. Another case is time-domain independence, i.e., PRS and CSIRS are transmitted on different OFDM symbols of the same slot, respectively, increasing the available reference signals to increase the duty cycle of the signals.
Because the last tracking result is adopted for initialization during each tracking, the tracking loop needs to minimize the prediction error as much as possible, and therefore, the section estimates and corrects the noise in the tracking process in real time. When the measurement noise covariance matrix R k becomes large, K k becomes small, resulting in a state correctionSmaller, posterior estimation/>Results are more biased towards a priori estimates/>Similarly, when the excess Cheng Zaosheng covariance matrix Q k-1 becomes larger,/>The corresponding K k becomes larger, resulting in a closer posterior estimation to the correction term. From this, the final state quantity of the Kalman filtering is closely related to R k and Q k-1, and the two are considered to be fixed in the traditional filtering model, and parameters which can accurately reflect the motion process and noise statistics of the receiver are adopted [18]. In each state prediction and measurement updating process, the observed noise is estimated and corrected in real time according to the signal carrier-to-noise ratio and the measurement residual error, and the Kalman filtering gain is dynamically adjusted.
Because of the characteristic of intermittent broadcasting of the 5G reference signal, the OFDM symbol without signal transmission is considered to only contain noise components, and coherent integration results on the OFDM symbol with signal transmission and the OFDM symbol without signal transmission are respectively analyzed to estimate the carrier-to-noise ratio of the signal. Namely:
Wherein the method comprises the steps of Representing the result of coherent integration over an OFDM symbol with signal transmission during the coherent integration time,Representing the result of coherent integration over an OFDM symbol without signal transmission. After the carrier-to-noise ratio is obtained, the carrier-to-noise ratio is substituted into formulas (15) and (19) and (20), so that the error variance of the discriminator is obtained, and real-time estimation of measurement noise is realized.
In order to realize stable tracking of the intermittent signal and reduce the influence of residual frequency offset on subcarriers on code phase, a signal tracking method based on KF is provided. The present invention simulates the code phase tracking error of a conventional PLL-aided based DLL tracking algorithm with the algorithms presented herein at different SNRs. The simulation scene is set to be from-15 dB to 25dB in signal-to-noise ratio, the step length is 5dB, the radio frequency carrier frequency f c =4 GHz, the receiver moves at a uniform speed, the speed v=20m/s, the maximum Doppler frequency offset between different subcarriers is 2Hz, and frequency offset compensation between different subcarriers is not carried out in the experiment. The results show that the tracking algorithm provided herein can also effectively track when the SNR is low.
PRS occupies 2/4/6/12 symbols in a slot, and Table 2 summarizes the code phase tracking error of PRS at these symbol duty cycles. Because the traditional DLL tracking algorithm adjusts the generation of the next local signal based on the last coherent integration result, the loop tracking result is greatly influenced by the duty ratio of the signal, and the tracking result has larger fluctuation along with the change of the duty ratio. The tracking algorithm provided by the invention dynamically adjusts the gain matrix by carrying out real-time estimation on noise once in each tracking process, so that more accurate tracking can be carried out under the condition of smaller signal duty ratio.
TABLE 2 code phase tracking error at different duty cycles
Furthermore, simulation experiments are carried out on the code phase tracking under different joint modes of the proposed reference signals, and under different SNR, the root mean square error condition of the code phase tracking is carried out. Where Case1 represents the tracking result when only PRS is used, and Case2 represents the frequency domain independent situation, that is, PRS and CSIRS occupy different subcarriers on 6 OFDM symbols in one slot. Case3 indicates that the time domains are independent, i.e. PRS and CSIRS occupy 6 OFDM symbols each in one slot. The results show that the tracking algorithm presented herein improves tracking accuracy to a different extent in different combinations than in conventional DLL tracking loops. And when the number of OFDM symbols occupied by the reference signal is increased, the signal interruption time is reduced, and the code phase tracking precision in a high dynamic environment is effectively improved.
Finally, a set of comparison experiments are provided herein to verify the effect of residual frequency offset between different subcarriers on the code phase tracking result. The system bandwidth is 100MHz, the subcarrier interval is 30KHz, the motion speed of the receiver is 100m/s, the frequency of the radio frequency carrier is 7GHz, and the Doppler frequency offset difference between the subcarrier with the highest frequency and the center subcarrier is 10Hz. Thus, during tracking, the step of compensating for the remaining frequency offset of the different sub-carriers in 3.3.1 is performed. The experimental result shows that the code phase tracking error after the frequency offset compensation is further reduced.
By analyzing signal systems of 5G downlink SSB and PRS, a CP-OFDM signal acquisition tracking loop design based on code phase under 5G standard is provided. The innovation point is that a CP-OFDM signal model under a tracking loop is deduced, and a traditional code phase discrimination function is modified. Meanwhile, aiming at the problem that Doppler frequency offset values on all subcarriers are different under 5G large bandwidth, residual frequency offset is compensated in the generation process of local signals in a tracking loop design part, and the influence on code phase estimation is reduced. Compared with the traditional DLL tracking loop, the result output by the discriminator is sent to the KF tracking loop, and the defect that the DLL loop cannot perform long-time coherent integration under intermittent signals is overcome. The paper finally provides that the PRS and the CSIRS are combined for tracking, the number of available reference signals is increased, and the observation noise in the KF tracking process is estimated and corrected in real time. Experimental results show that the tracking loop design proposed herein can effectively reduce code phase ranging errors. Further research is then required to complete acquisition tracking and position location solutions for signals at multiple base stations, and the effect of time synchronization errors between base stations is also considered in this part of the work.
The foregoing embodiments of the present invention are not intended to limit the technical scope of the present invention, and therefore, any minor modifications, equivalent variations and modifications made to the above embodiments according to the technical principles of the present invention still fall within the scope of the technical proposal of the present invention.
Claims (5)
1. A5G downlink signal intermittent tracking method is characterized in that: the method comprises the following steps:
Step 1, receiving a 5G signal, wherein the 5G signal comprises an on phase and an off phase;
step 2, searching the cells;
step 3, performing coherent integration on the processed 5G signal and the local signal to obtain coherent integration results of the instant branch, the advanced branch and the lagging branch;
Step 4, sending the coherent integration result to a discriminator for processing: for the on-phase 5G signal, the discriminator outputs a code phase error discrimination function Carrier phase error discrimination function/>And carrier frequency error discrimination function/>; Then, the signal-to-noise ratio of the 5G signal is estimated according to the coherent integration result in the on phase and the coherent integration result in the off phase, and the code phase covariance/> is calculated according to the signal-to-noise ratioCarrier phase covariance/>And carrier frequency covariance/>；
Step 5, the output of the discriminator is sent into a Kalman filter, and the Kalman filter predicts and corrects the state;
And (3) predicting the state to obtain:
；
Wherein, A priori estimating vector for the system state at the current moment;
estimating a vector for a posterior of the system state at a previous time;
F is the state transition matrix of the system state vector at two adjacent moments,
；
Is the coherent integration time;
estimating an error covariance matrix for the prior of the current moment;
Estimating an error covariance matrix for the posterior at the previous moment;
the process noise covariance matrix of the last moment;
The state prediction and correction are carried out to obtain:
；
Wherein, The Kalman filtering gain at the current moment;
h is the observation matrix of the sample, ；
For measuring noise covariance matrix,/>；
Estimating a vector for a posterior of the current system state;
For observing vectors, composed of discriminator output results, i.e./> ；
Estimating an error covariance matrix for a posterior at the current moment;
Step 6, outputting the code phase error of the next moment by the Kalman filter Carrier phase error/>Carrier frequency error/>And sent to a reference signal generator.
2. The method for intermittent tracking of a 5G downlink signal according to claim 1, wherein the method comprises the steps of: the step 2 specifically comprises the following steps:
Firstly, the received signal and 3 groups of local PSS signals are subjected to related estimation to determine I.e. cell identification number; the calculation of the correlation estimate is shown in the following formula, wherein/>For receiving signals,/>For local PSS signal,/>Representing a correlation operation:
；
the position of the correlation peak represents the SSB symbol start time for controlling the FFT window;
Frequency offset estimation based on CP, wherein As the number of samples within the length of the CP,
After obtaining the initial frequency offset, carrying out frequency offset compensation on the received signal to obtain
Represents the sampling interval, satisfies/>，/>For an OFDM symbol effective duration;
Then receives the signal Performing FFT operation, extracting SSB resource grid signal, and performing correlation estimation with local 336 SSS, to obtain SSS sequence ID with maximum correlation peak value as cell group ID/>；
Obtaining the cell ID number of the base stationThereafter, local PRS and CSIRS signals are generated, and the received signalsPerforming correlation estimation to obtain a signal/>。
3. The method for intermittent tracking of a 5G downlink signal according to claim 2, wherein: and step 2, adopting a channel and time delay joint estimation algorithm, wherein a processed signal model is as follows:
Wherein the method comprises the steps of The symbol of the first subcarrier at the k moment;
。
4. A method for intermittent tracking of a 5G downlink signal according to claim 3, wherein: in the step (3) of the above-mentioned process,
The instantaneous branch coherent integration results are:
P is complex, the real part of P is expressed as The imaginary part of P is expressed as/>Namely there is/>；
The result of the advanced branch coherent integration is:
；
the lag branch coherent integration results are:
。
5. The method for intermittent tracking of 5G downlink signals according to claim 4, wherein: in the step 4 of the above-mentioned process,
The code phase error discrimination function is；
The carrier phase error discrimination function is；
The carrier frequency error discrimination function isWherein, the method comprises the steps of, wherein,
；
The coherent integration result in the on phase is further recorded asThe result of the coherent integration in the off phase is further denoted as/>; The carrier-to-noise ratio of the 5G signal is
Wherein,Representing the result of coherent integration in the on phase,/>A coherent integration result representing an off phase;
code phase covariance is ；
Carrier phase covariance is；
And carrier frequency covariance。
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